电力系统及其自动化学报2017，Vol.29Issue(6)：118-123,6.DOI:10.3969/j.issn.1003-8930.2017.06.019
结合相似日GA-BP神经网络的光伏发电预测
PV Generation Forecasting Combined with Similar Days and GA-BP Neural Network
耿博 1高贞彦 2白恒远 1何维 1董文杰 2赵友国2
作者信息
- 1. 深圳供电局有限公司,深圳 518000
- 2. 东方电子股份有限公司,烟台 264000
- 折叠
摘要
Abstract
In order to forecast the photovoltaic(PV)power generation with high accuracy and reduce the impact of grid-connected PV system on power system,the concept of similar day is introduced in this paper to analyze the weather in-formation on the prediction day. According to the data such as weather and seasonal information,the historical genera-tion data and weather data which have similar characteristics to those on the prediction day are chosen from historical data through the clustering method,and they are further used as training samples for the prediction model. Moreover, genetic algorithm-back propagation(GA-BP)neural network is used to establish the prediction model and forecast the PV power generation. The proposed method is verified based on the actual data of a PV system,and the forecasting er-ror is calculated. The analysis results show that the forecasting method has higher prediction accuracy.关键词
光伏/发电/预测/相似日/神经网络Key words
photovoltaic/generation/forecasting/similar day/neural network分类
信息技术与安全科学引用本文复制引用
耿博,高贞彦,白恒远,何维,董文杰,赵友国..结合相似日GA-BP神经网络的光伏发电预测[J].电力系统及其自动化学报,2017,29(6):118-123,6.
